The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
BayCANN: Streamlining Bayesian Calibration With Artificial Neural Network Metamodeling
|
|---|---|
| Published in |
Frontiers in Physiology, May 2021
|
| DOI | 10.3389/fphys.2021.662314 |
| Pubmed ID | |
| Authors |
Hawre Jalal, Thomas A. Trikalinos, Fernando Alarid-Escudero |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 25% |
| Netherlands | 1 | 8% |
| United Kingdom | 1 | 8% |
| Switzerland | 1 | 8% |
| Unknown | 6 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 58% |
| Scientists | 5 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 24% |
| Student > Ph. D. Student | 4 | 16% |
| Student > Bachelor | 2 | 8% |
| Professor | 2 | 8% |
| Student > Master | 2 | 8% |
| Other | 4 | 16% |
| Unknown | 5 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 20% |
| Decision Sciences | 3 | 12% |
| Computer Science | 3 | 12% |
| Economics, Econometrics and Finance | 2 | 8% |
| Agricultural and Biological Sciences | 1 | 4% |
| Other | 5 | 20% |
| Unknown | 6 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 June 2021.
All research outputs
#4,448,155
of 22,973,051 outputs
Outputs from Frontiers in Physiology
#2,191
of 13,723 outputs
Outputs of similar age
#106,666
of 445,900 outputs
Outputs of similar age from Frontiers in Physiology
#79
of 547 outputs
Altmetric has tracked 22,973,051 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,723 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 445,900 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 547 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.